Simulation and Empirical Studies of Long Short-Term Memory Performance to Deal with Limited Data by Khusnia Nurul Khikmah, Kusman Sadik, Khairil Anwar Notodiputro

“…The approach method chosen is long short-term memory (LSTM), a development of recurrent neural network (RNN). Another problem is the availability of data, which is not limited to high-dimensional data but also limited data. …”
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Indoor High Precision Three-Dimensional Positioning System Based on Visible Light Communication Using Improved Hybrid Bat Algorithm by Yong Chen, Han Zheng, Huanlin Liu, Zhaozhong Han, Zhimiao Ren

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Research on leaf identification of table grape varieties based on deep learning by PAN Bowen, LIN Meiling, JU Yanlun, SU Baofeng, SUN Lei, FAN Xiucai, ZHANG Ying, ZHANG Yonghui, LIU Chonghuai, JIANG Jianfu, FANG Yulin

“…In the realm of automatic recognition, four distinct convolutional neural network models were deployed: GoogleNet, ResNet-50, ResNet-101, and VGG-16. …”
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Design of real-time transmission system for underwater panoramic camera based on RTSP. by Wenhui Wang, Yongqi Li, Rufei He

“…The congestion control method using RTCP feedback monitors the network status in real-time and dynamically adjusts the data transmission rate, effectively avoiding the occurrence of network congestion problems. …”
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Robot Visual Tracking Model Based on Improved GOTURN-LD Algorithm by Lijuan Xu, Dalong Liu, Huanjian Ma

“…As the key performance of visual tracking, it still has the problems of low tracking accuracy and poor real-time performance. …”
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A Fine-Grained Aircraft Target Recognition Algorithm for Remote Sensing Images Based on YOLOV8 by Xiao-Nan Jiang, Xiang-Qian Niu, Fan-Lu Wu, Yao Fu, He Bao, Yan-Chao Fan, Yu Zhang, Jun-Yan Pei

“…Initially, this article designs a local detail feature module to tackle the problem of information loss in shallow networks. This module enhances the capture of semantic information while extracting shallow features, thereby preserving more fine-grained features and improving the network's feature extraction capability. …”
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Outdoor Clothing Design for Traffic Safety Based on Big Data and Artificial Intelligence by Ya Zhou, Yun Shi

“…The results obtained are as follows: the predicted value of the DBN neural network is the closest to the actual value, the average prediction accuracy of DBN for the cuff size is 90%, and the average prediction accuracy for the neck circumference is 91.5%. …”
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A Multi-Modal Attentive Framework That Can Interpret Text (MMAT) by Vijay Kumari, Sarthak Gupta, Yashvardhan Sharma, Lavika Goel

“…The proposed model uses the dynamic pointer network instead of classification for iterative answer prediction with a focal loss function to overcome the class imbalance problem. …”
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The First Step of AI in LEO SOPs: DRL-Driven Epoch Credibility Evaluation to Enhance Opportunistic Positioning Accuracy by Jiaqi Yin, Feilong Li, Ruidan Luo, Xiao Chen, Linhui Zhao, Hong Yuan, Guang Yang

“…We developed a novel Markov Decision Process (MDP) model to assist the agent in addressing the epoch weighting problem and trained the agent utilizing the Double Deep Q-Network (DDQN) algorithm on 107 h of Iridium signal data. …”
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Cross-Receiver Radio Frequency Fingerprint Identification: A Source-Free Adaptation Approach by Jian Yang, Shaoxian Zhu, Zhongyi Wen, Qiang Li

“…We propose a novel approach called contrastive source-free cross-receiver network (CSCNet), which employs contrastive learning to facilitate model adaptation using only unlabeled data from the deployed receiver. …”
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A marine ship detection method for super-resolution SAR images based on hierarchical multi-scale Mask R-CNN by Jiancong Fan, Miaoxin Guo, Lei Zhang, Jianjun Liu, Jianjun Liu, Yang Li, Yang Li

“…Firstly, a TaylorGAN super-resolution network is designed, and the TaylorShift attention mechanism is introduced to enhance the generator’s ability to restore the edge and texture details of the ship. …”
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Deep Reinforcement Learning for Optimal Replenishment in Stochastic Assembly Systems by Lativa Sid Ahmed Abdellahi, Zeinebou Zoubeir, Yahya Mohamed, Ahmedou Haouba, Sidi Hmetty

“…The Deep Q-Network (DQN) algorithm is adapted and employed to learn optimal replenishment policies over a fixed planning horizon. …”
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SAVL: Scene-Adaptive UAV Visual Localization Using Sparse Feature Extraction and Incremental Descriptor Mapping by Ganchao Liu, Zhengxi Li, Qiang Gao, Yuan Yuan

“…The results on the dataset indicate that the proposed method achieves excellent positioning accuracy, with an average error of only 8.71 m.…”
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Relationship Between Virtual Pharmacology Lecture, Attendance and Performance: Personal Experience With Veterinary Students of the University of BUEA, Southwest Cameroon by Saganuwan Alhaji Saganuwan, Manchang Tanyi Kingsley

“…The failure of power supply, problems of coordinating courses, zoom meeting network issues, insufficient laptops and phones, as well as the problem of connection with the course lecturer for the online lectures are disadvantages. …”
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DeepMethyGene: a deep-learning model to predict gene expression using DNA methylations by Yuyao Yan, Xinyi Chai, Jiajun Liu, Sijia Wang, Wenran Li, Tao Huang

“…Our model transforms methylation Beta values to M values for Gaussian distributed data optimization, dynamically adjusts the output channels according to input dimension, and implements residual blocks to mitigate the problem of gradient vanishing when training very deep networks. …”
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Efficacy of a mindful-eating programme to reduce emotional eating in patients suffering from overweight or obesity in primary care settings: a cluster-randomised trial protocol by Jesus Montero-Marin, Mayte Navarro-Gil, Paola Herrera-Mercadal, Alberto Barcelo-Soler, Javier Garcia-Campayo, Hector Morillo Sarto, Bianca Pantilie

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Improved model MASW YOLO for small target detection in UAV images based on YOLOv8 by Xianghe Meng, Fei Yuan, Dexiang Zhang

“…Experiments conducted on the VisDrone2019 dataset demonstrate that the average detection accuracy of the MASW-YOLO algorithm is 38.3%, which is augmented by 7.9% through the utilisation of the original YOLOv8n network. …”
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YOLO-RDM: A high accuracy and efficient algorithm for magnetic tile surface defect detection with practical applications. by Wei Niu, Cheng Lv, Enxu Zhang, Zhongbin Wei

“…Finally, we replace the original backbone network of YOLOv8 with the MogaNet network. MogaNet is a module that aggregates contextual information, enhancing the network's discriminative power, learning efficiency, and ability to capture defect features in images. …”
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Improved double DQN with deep reinforcement learning for UAV indoor autonomous obstacle avoidance by Ruiqi Yu, Qingdang Li, Jiewei Ji, Tingting Wu, Jian Mao, Shun Liu, Zhen Sun

“…Abstract Aiming at the problems of insufficient autonomous obstacle avoidance performance of UAVs in complex indoor environments, an improved Double DQN algorithm based on deep reinforcement learning is proposed. …”
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Surface defect detection model of laser cutting polycrystalline cubic boron nitride tool based on asymptotic fusion strategy by Anfu Zhu, Jiaxiao Xie, Heng Guo, Jie Wang, Zilong Guo, Lei Xu, SiXin Zhu, Zhanping Yang, Bin Wang

“…The experimental results based on the self-constructed laser-cutting polycrystalline cubic boron nitride tool surface defects dataset show that the average accuracy of the AFFS-YOLO model is improved by 5.6% compared with that of the YOLOv5 model, reaching 86.1%, and the detection effect is better than that of the original network and other classical target detection networks.…”
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